A fuzzy logic-based predictor for predictive coding of images

In this paper, we present a fuzzy logic-based nonlinear predictor for predictive coding of images. We define five local structure patterns of images: uniform area, horizontal contour (0 degrees), vertical contour (90 degrees), 45 degrees, and 135 degrees diagonal contours. Their membership functions are derived with the gradient-based edge detection method and predicted values for different patterns are defined by linear extrapolation from available neighborhood pixel values. The predicted value of the current pixel can be obtained based on the membership functions and the defined predicted values for the different patterns, A set of parameters to characterize the proposed fuzzy predictor are determined from empirical data. Success in the use of the proposed predictor is demonstrated, by using simulation results through the reduction in the entropy as compared to those of existing linear and nonlinear ones, It is also shown that the proposed fuzzy predictor can be efficiently implemented.